Optical communication based on the periodic nonlinear Fourier transform signal processing

In this work we introduce the periodic nonlinear Fourier transform (PNFT) and propose a proof-of-concept communication system based on it by using a simple waveform with known nonlinear spectrum (NS). We study the performance (addressing the bit-error-rate (BER), as a function of the propagation distance) of the transmission system based on the use of the PNFT processing method and show the benefits of the latter approach. By analysing our simulation results for the system with lumped amplification, we demonstrate the decent potential of the new processing method.

Fault diagnosis scheme for open-circuit faults in switched reluctance motor drives using fast Fourier transform algorithm with bus current detection

Reliability of power converters is of crucial importance in switched reluctance motor drives used for safety-critical applications. Open-circuit faults in power converters will cause the motor to run in unbalanced states, and if left untreated, they will lead to damage to the motor and power modules, and even cause a catastrophic failure of the whole drive system. This study is focused on using a single current sensor to detect open-circuit faults accurately. An asymmetrical half-bridge converter is considered in this study and the faults of single-phase open and two-phase open are analysed. Three different bus positions are defined. On the basis of a fast Fourier transform algorithm with Blackman window interpolation, the bus current spectrums before and after open-circuit faults are analysed in details. Their fault characteristics are extracted accurately by the normalisations of the phase fundamental frequency component and double phase fundamental frequency component, and the fault characteristics of the three bus detection schemes are also compared. The open-circuit faults can be located by finding the relationship between the bus current and rotor position. The effectiveness of the proposed diagnosis method is validated by the simulation results and experimental tests.

Proteção diferencial de transformadores de potência utilizando a transformada Wavelet

About 10% of faults involving the electrical system occurs in power transformers. Therefore, the protection applied to the power transformers is essential to ensure the continuous operation of this device and the efficiency of the electrical system. Among the protection functions applied to power transformers, the differential protection appears as one of the main schemes, presenting reliable discrimination between internal faults and external faults or inrush currents. However, when using the low frequency components of the differential currents flowing through the transformer, the main difficulty of the conventional methods of differential protection is the delay for detection of the events. However, internal faults, external faults and other disturbances related to the transformer operation present transient and can be appropriately detected by the wavelet transform. In this paper is proposed the development of a wavelet-based differential protection for detection and identification of external faults to the transformer, internal faults, and transformer energizing by using the wavelet coefficient energy of the differential currents. The obtained results reveal the advantages of using of the wavelet transform in the differential protection compared to conventional protection, since it provides reliability and speed in detection of these events.

Síntese e caracterização de materiais mesoporosos para a captura de CO2: influência do óxido de níquel

Several materials are currently under study for the CO2 capture process, like the metal oxides and mixed metal oxides, zeolites, carbonaceous materials, metal-organic frameworks (MOF's) organosilica and modified silica surfaces. In this work, evaluated the adsorption capacity of CO2 in mesoporous materials of different structures, such as MCM-48 and SBA- 15 without impregnating and impregnated with nickel in the proportions 5 %, 10 % and 20 % (m/m), known as 5Ni-MCM-48, 10Ni-MCM-48, 20Ni-MCM-48 and 5Ni-SBA-15, 10NiSBA-15, 20Ni-SBA-15. The materials were characterized by means of X-ray diffraction (XRD), thermal analysis (TG and DTG), Fourier transform infrared spectroscopy (FT-IR), N2 adsorption and desorption (BET) and scanning electron microscopy (SEM) with EDS. The adsorption process was performed varying the pressure of 100 - 4000 kPa and keeping the temperature constant and equal to 298 K. At a pressure of 100 kPa, higher concentrations of adsorption occurred for the materials 5Ni-MCM-48 (0.795 mmol g-1 ) and SBA-15 (0.914 mmol g-1 ) is not impregnated, and at a pressure of 4000 kPa for MCM-48 materials (14.89 mmol g-1) and SBA-15 (9.97 mmol g-1) not impregnated. The results showed that the adsorption capacity varies positively with the specific area, however, has a direct dependency on the type and geometry of the porous structure of channels. The data were fitted using the Langmuir and Freundlich models and were evaluated thermodynamic parameters Gibbs free energy and entropy of the adsorption system

Uso de metamaterial em antenas de microfita com supercondutor

Metamaterials have attracted great attention in recent decades, due to their electromagnetic properties which are not found in nature. Since metamaterials are now synthesized by the insertion of artificially manufactured inclusions in a specified homogeneous medium, it became possible for the researcher to work with a wide collection of independent parameters, for example, the electromagnetic properties of the material. An investigation of the properties of ring resonators was performed as well as those of metamaterials. A study of the major theories that clearly explain superconductivity was presented. The BCS theory, London Equations and the Two-Fluid Model are theories that support the application of superconducting microstrip antennas. Therefore, this thesis presents theoretical, numerical and experimental-computational analysis using full-wave formalism, through the application of the Transverse Transmission Line – LTT method applied in the Fourier Transform Domain (FTD). The LTT is a full wave method, which, as a rule, obtains the electromagnetic fields in terms of the transverse components of the structure. The inclusion of the superconducting patch is performed using the complex resistive boundary condition. Results of resonant frequency as a function of antenna parameters are obtained. To validate the analysis, computer programs were developed using Fortran, simulations were created using the commercial software, with curves being drawn using commercial software and MATLAB, in addition to comparing the conventional patch with the superconductor as well as comparing a metamaterial substrate with a conventional one, joining the substrate with the patch, observing what improves on both cas

Encapsulamento de solventes em nanotubos de haloisita para promoção de auto-reparo em polímeros

Micro cracking during service is a critical problem in polymer structures and polymer composite materials. Self-healing materials are able to repair micro cracks, thus their preventing propagation and catastrophic failure of structural components. One of the self-healing approaches presented in the literature involves the use of solvents which react with the polymer. The objective of this research is to investigate a procedure to encapsulate solvents in halloysite nanotubes to promote self-healing ability in epoxy. Healing is triggered by crack propagation through embedded nanotubes in the polymer, which then release the liquid sovent into the crack plane. Two solvents were considered in this work: dimethylsulfoxide (DMSO) and nitrobenzene. The nanotubes were coated using the layer-by-layer technique of oppositely charged polyelectrolytes: cetyltrimethylammonium bromide (CTAB) and sodium polyacrylate. Solvent encapsulation was verified by X-ray diffraction (XRD), Fourier transform infrared (FTIR), analysis thermogravimetry (TGA), adsorption and desorption of nitrogen and scanning electron microscopy (SEM). The introduction of the solvent DMSO into the cavity of the nanotubes was confirmed by the techniques employed. However, was not verified with nitrobenzene only promoted clay aggregation. The results suggest that the CTAB reacted with the halloystite to form a sealing layer on the surface of the nanotubes, thus encapsulating the solvent, while this was not verified using sodium polyacrylate.

Detecção e diagnostico de agarramento em válvulas posicionadoras

Valve stiction, or static friction, in control loops is a common problem in modern industrial processes. Recently, many studies have been developed to understand, reproduce and detect such problem, but quantification still remains a challenge. Since the valve position (mv) is normally unknown in an industrial process, the main challenge is to diagnose stiction knowing only the output signals of the process (pv) and the control signal (op). This paper presents an Artificial Neural Network approach in order to detect and quantify the amount of static friction using only the pv and op information. Different methods for preprocessing the training set of the neural network are presented. Those methods are based on the calculation of centroid and Fourier Transform. The proposal is validated using a simulated process and the results show a satisfactory measurement of stiction.

Desenvolvimento de um material têxtil termosenssível com micro/nanocápsulas imobilizadas em fibras regeneradas

Intelligent and functional Textile Materials have been widely developed and researched with the purpose of being used in several areas of science and technology. These fibrous materials require different chemical and physical properties to obtain a multifunctional material. With the advent of nanotechnology, the techniques developed, being used as essential tools to characterize these new materials qualitatively. Lately the application of micro and nanomaterials in textile substrates has been the objective of many studies, but many of these nanomaterials have not been optimized for their application, which has resulted in increased costs and environmental pollution, because there is still no satisfactory effluent treatment available for these nanomaterials. Soybean fiber has low adsorption for thermosensitive micro and nanocapsules due to their incompatibility of their surface charges. For this reason, in this work initially chitosan was synthesized to functionalise soybean fibres. Chitosan is a natural polyelectrolyte with a high density of positive charges, these fibres have negative charges as well as the micro/nanocápsules, for this reason the chitosan acts as auxiliary agent to cationize in order to fix the thermosensitive microcapsules in the textile substrate. Polyelectrolyte was characterized using particle size analyses and the measurement of zeta potential. For the morphological analysis scanning Electron Microscopy (SEM) and x-Ray Diffraction (XRD) and to study the thermal properties, thermogravimetric analysis (TGA), Differential Scanning Calorimetry (DSC), Near Infrared Spectroscopy analysis in the Region of the Fourier Transform Infrared (FTIR), colourimetry using UV-VIS spectrum were simultaneously performed on the substrate. From the measurement of zeta potential and in the determination of the particle size, stability of electrostatic chitosan was observed around 31.55mV and 291.0 nm respectively. The result obtained with (GD) for chitosan extracted from shrimp was 70 %, which according to the literature survey can be considered as chitosan. To optimize the dyeing process a statistical software, Design expert was used. The surface functionalisation of textile substrate with 2% chitosan showed the best result of K/S, being the parameter used for the experimental design, in which this showed the best response of dyeing absorbance in the range of 2.624. It was noted that soy knitting dyed with the thermosensitive micro andnanocapsules property showed excellent washing solidity, which was observed after 25 home washes, and significant K/S values.

Tratamento de argila montmorilonítica para a produção de nanocompósitos poliméricos com retardo de propagação de chama

Compared to conventional composites, polymer matrix nanocomposites typically exhibit enhanced properties at a significantly lower filler volume fraction. Studies published in the literature indicate t hat the addition of nanosilicate s can increase the resistance to flame propagation in polymers. In this work, a treatment of montmorillonite (MMT) nano clay and the effect of its ad dition o n flame propagation characteristics of vinyl ester were studied. The resea rch was conducted in two stages. The first stage focused on the purification and activation of the MMT clay collected from a natural deposit to improve compatibility with the polymer matrix . Clay modification with sodium acetate was also studied to improve particle dispersion in the polymer. The second step was focused on the effect of the addition of the treated clay on nanocomposites ’ properties. Nanocomposites with clay con tents of 1, 2, 4 wt. % were processed. T he techniques for the characterization of the clay included X - ray fluorescence (XRF), X - r ay d iffraction (XRD), thermogravimetric a nalysis (TGA), d ifferential scanning c alorimetry (DSC) , s urface area (BET) and Fourier transform infrared spectroscopy (FTIR). For t he characterization of the nanocomposites , the techniques used were thermogravimetric a nalysis (TGA) , differential scanning c alorimetry (DSC), Fourier transform infrared spectroscopy (FTIR) , scanning electron mi croscopy (SEM), transmission electron m icroscopy (TEM), and the determination of tensile strength, modulus of elasticity and resistance to flame propagation. According to the results, the purification and activation treatment with freeze - drying used in thi s work for the montmorillonite clay was efficient to promote compatibility and dispersion in the polymer matrix as evidenced by the characterization of the nanocomposite s . It was also observed that the clay modifica tion using sodium acetate did not produce any significant effect to improve compatibilization of the clay with the polymer. The addition of the treated MMT resulted in a reduction of up to 53% in the polymer flame propagation speed and did not affect the mechanical tensile strength and modulus o f elas ticity of the polymer, indicating compatibility between the clay and polymer. The effectiveness in reducing flame propagation speed peaked for nanocomposites with 2 wt. % clay, indicating that this is the optimum clay concentration for this property. T he clay treatment used in this work enables the production of vinylester matrix nanocomposites with flame - retardancy properties .

Utilização da cinza da casca de arroz em cimentação de poços de petróleo

Pozzolanic materials such as rice husk ash are widely used to substitute part of cement, because they react with calcium hydroxide (CH) producing calcium silicate hydrate (C-S-H), which aggregate better physical, chemical and mechanical properties to the cement slurry. The usage of rice husk biomass ash from agribusiness in addition to or partially replacing cement is a noble purpose and a good way of sustainable development which currently is an obsession around the world. The ashes utilized in this study were characterized by: scanning electron microscopy technique (SEM), Fourier transform infrared spectroscopy (FTIR), Energy-dispersive X-ray spectroscopy (EDX) and BET method. The pozzolanic activity of RHA and WRHA in cement slurries was evaluated by: thermal-gravimetric technique and derivative thermogravimetry (TGA/DTG), X-ray diffraction (XRD) and Compressive Strength. The slurries formulated with additions of 10% and 20% of RHA and WRHA were cured for 28 days at 58 °C. The results of thermal analysis demonstrated that a 20% WRHA addition caused a reduction of approximately 73% of Portlandite (calcium hydroxide – CH) phase related to standard slurry (STD). The XRD scans also demonstrated the reduction of the Portlandite peaks’ intensity for each slurry compared with STD slurry. The RHA and WRHA react chemically with Portlandite producing calcium silicate hydrate (C-S-H), confirming their effect as a pozzolanic agent. The WRHA presented the best results as a pozzolanic material.

Classificador máquina de suporte vetorial com análise de Fourier aplicada em dados de EEG e EMG

The classifier support vector machine is used in several problems in various areas of knowledge. Basically the method used in this classier is to end the hyperplane that maximizes the distance between the groups, to increase the generalization of the classifier. In this work, we treated some problems of binary classification of data obtained by electroencephalography (EEG) and electromyography (EMG) using Support Vector Machine with some complementary techniques, such as: Principal Component Analysis to identify the active regions of the brain, the periodogram method which is obtained by Fourier analysis to help discriminate between groups and Simple Moving Average to eliminate some of the existing noise in the data. It was developed two functions in the software R, for the realization of training tasks and classification. Also, it was proposed two weights systems and a summarized measure to help on deciding in classification of groups. The application of these techniques, weights and the summarized measure in the classier, showed quite satisfactory results, where the best results were an average rate of 95.31% to visual stimuli data, 100% of correct classification for epilepsy data and rates of 91.22% and 96.89% to object motion data for two subjects.

Estudo de famílias wavelets para aplicação na análise em DOAS

Trace gases are important to our environment even though their presence comes only by ‘traces’, but their concentrations must be monitored, so any necessary interventions can be done at the right time. There are some lower and upper boundaries which produce nice conditions for our lives and then monitoring trace gases comes as an essential task nowadays to be accomplished by many techniques. One of them is the differential optical absorption spectroscopy (DOAS), which consists mathematically on a regression - the classical method uses least-squares - to retrieve the trace gases concentrations. In order to achieve better results, many works have tried out different techniques instead of the classical approach. Some have tried to preprocess the signals to be analyzed by a denoising procedure - e.g. discrete wavelet transform (DWT). This work presents a semi-empirical study to find out the most suitable DWT family to be used in this denoising. The search seeks among many well-known families the one to better remove the noise, keeping the original signal’s main features, then by decreasing the noise, the residual left after the regression is done decreases too. The analysis take account the wavelet decomposition level, the threshold to be applied on the detail coefficients and how to apply them - hard or soft thresholding. The signals used come from an open and online data base which contains characteristic signals from some trace gases usually studied.

Estudo de famílias wavelets para aplicação na análise em DOAS

Trace gases are important to our environment even though their presence comes only by ‘traces’, but their concentrations must be monitored, so any necessary interventions can be done at the right time. There are some lower and upper boundaries which produce nice conditions for our lives and then monitoring trace gases comes as an essential task nowadays to be accomplished by many techniques. One of them is the differential optical absorption spectroscopy (DOAS), which consists mathematically on a regression - the classical method uses least-squares - to retrieve the trace gases concentrations. In order to achieve better results, many works have tried out different techniques instead of the classical approach. Some have tried to preprocess the signals to be analyzed by a denoising procedure - e.g. discrete wavelet transform (DWT). This work presents a semi-empirical study to find out the most suitable DWT family to be used in this denoising. The search seeks among many well-known families the one to better remove the noise, keeping the original signal’s main features, then by decreasing the noise, the residual left after the regression is done decreases too. The analysis take account the wavelet decomposition level, the threshold to be applied on the detail coefficients and how to apply them - hard or soft thresholding. The signals used come from an open and online data base which contains characteristic signals from some trace gases usually studied.

Sistema inteligente para o processamento de imagens digitais intrabucais oclusais

Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

Sistema inteligente para o processamento de imagens digitais intrabucais oclusais

Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.